{"title":"Structure-Activity Relationship Studies on VEGFR2 Tyrosine Kinase Inhibitors for Identification of Potential Natural Anticancer Compounds.","authors":"Meenakshi Verma, Aqib Sarfraz, Inamul Hasan, Prema Gauri Vasudev, Feroz Khan","doi":"10.2174/0115734064247526231129080415","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>Over-expression of Vascular Endothelial Growth Factor Receptors (VEGFRs) leads to the hyperactivation of oncogenes. For inhibition of this hyperactivation, the USA Food Drug Administration (FDA) has approved many drugs that show adverse effects, such as hypertension, hypothyroidism, etc. There is a need to discover potent natural compounds that show minimal side effects. In the present study, we have taken structurally diverse known VEGFR2 inhibitors to develop a Quantitative Structure-Activity Relationship (QSAR) model and used this model to predict the inhibitory activity of natural compounds for VEGFR2.</p><p><strong>Methods: </strong>The QSAR model was developed through the forward stepwise Multiple Linear Regression (MLR) method. A developed QSAR model was used to predict the inhibitory activity of natural compounds. Absorption, Distribution, Metabolism, Excretion, and Toxicity (ADMET) assessment and molecular docking studies were performed. The binding stability of the natural compounds with VEGFR2 was elucidated through Molecular Dynamics (MD) simulation.</p><p><strong>Results: </strong>The developed QSAR model against VEGFR2 showed the regression coefficient of the training dataset (r<sup>2</sup>) as 0.81 and the external regression coefficient of the test dataset (r2 test) 0.71. Descriptors, viz., electro-topological state of potential hydrogen bonds (maxHBint2, nHBint6), atom types (minssNH), maximum topological distance matrix (SpMAD_Dt), and 2D autocorrelation (ATSC7v), have been identified. Using this model, 14 natural compounds have been selected that have shown inhibitory activity for VEGFR2, of which six natural compounds have been found to possess a strong binding affinity with VEGFR2. In MD simulation, four complexes have shown binding stability up to 50ns.</p><p><strong>Conclusion: </strong>The developed QSAR model has identified 5 conserved activity-inducing physiochemical properties, which have been found to be correlated with the anticancer activity of the nonidentical ligand molecules bound with the VEGFR2 kinase. Lavendustin_A, 3'-O-acetylhamaudol, and arctigenin have been obtained as possible lead natural compounds against the VEGFR2 kinase.</p>","PeriodicalId":18382,"journal":{"name":"Medicinal Chemistry","volume":" ","pages":"646-661"},"PeriodicalIF":1.9000,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Medicinal Chemistry","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.2174/0115734064247526231129080415","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"CHEMISTRY, MEDICINAL","Score":null,"Total":0}
引用次数: 0
Abstract
Background: Over-expression of Vascular Endothelial Growth Factor Receptors (VEGFRs) leads to the hyperactivation of oncogenes. For inhibition of this hyperactivation, the USA Food Drug Administration (FDA) has approved many drugs that show adverse effects, such as hypertension, hypothyroidism, etc. There is a need to discover potent natural compounds that show minimal side effects. In the present study, we have taken structurally diverse known VEGFR2 inhibitors to develop a Quantitative Structure-Activity Relationship (QSAR) model and used this model to predict the inhibitory activity of natural compounds for VEGFR2.
Methods: The QSAR model was developed through the forward stepwise Multiple Linear Regression (MLR) method. A developed QSAR model was used to predict the inhibitory activity of natural compounds. Absorption, Distribution, Metabolism, Excretion, and Toxicity (ADMET) assessment and molecular docking studies were performed. The binding stability of the natural compounds with VEGFR2 was elucidated through Molecular Dynamics (MD) simulation.
Results: The developed QSAR model against VEGFR2 showed the regression coefficient of the training dataset (r2) as 0.81 and the external regression coefficient of the test dataset (r2 test) 0.71. Descriptors, viz., electro-topological state of potential hydrogen bonds (maxHBint2, nHBint6), atom types (minssNH), maximum topological distance matrix (SpMAD_Dt), and 2D autocorrelation (ATSC7v), have been identified. Using this model, 14 natural compounds have been selected that have shown inhibitory activity for VEGFR2, of which six natural compounds have been found to possess a strong binding affinity with VEGFR2. In MD simulation, four complexes have shown binding stability up to 50ns.
Conclusion: The developed QSAR model has identified 5 conserved activity-inducing physiochemical properties, which have been found to be correlated with the anticancer activity of the nonidentical ligand molecules bound with the VEGFR2 kinase. Lavendustin_A, 3'-O-acetylhamaudol, and arctigenin have been obtained as possible lead natural compounds against the VEGFR2 kinase.
期刊介绍:
Aims & Scope
Medicinal Chemistry a peer-reviewed journal, aims to cover all the latest outstanding developments in medicinal chemistry and rational drug design. The journal publishes original research, mini-review articles and guest edited thematic issues covering recent research and developments in the field. Articles are published rapidly by taking full advantage of Internet technology for both the submission and peer review of manuscripts. Medicinal Chemistry is an essential journal for all involved in drug design and discovery.